Backstepping control of uncertain time delay systems based on neural network

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Abstract

In this paper, a robust adaptive control scheme is proposed for a class of uncertain MIMO time delay systems based on backstepping method with Radical basis function(RBF) neural network. The system uncertainty is approximated by RBF neural networks, and a parameter update law is presented for approximating the system uncertainty. In each step, the control scheme is derived in terms of linear matrix inequalities (LMI's). A robust adaptive controller is designed using backstepping and LMI method based on the output of the RBF neural networks. Finally, an example is given to illustrate the availability of the proposed control scheme. © Springer-Verlag Berlin Heidelberg 2007.

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Chen, M., Jiang, C. S., Wu, Q. X., & Chen, W. H. (2007). Backstepping control of uncertain time delay systems based on neural network. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4491 LNCS, pp. 112–121). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_15

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